罐采样/气相色谱-质谱法分析环境空气中57种臭氧前体物

针对中国当前臭氧污染问题,建立了苏玛罐采样-低温浓缩/气相色谱-质谱法分析环境空气中57种臭氧前体物的方法。样品经三级冷阱预浓缩仪富集、除干扰组分并进行冷聚焦后利用冷柱温分离,气相色谱-质谱法分析。笔者优化了阱的关键温度和时间参数,在最佳实验条件下进行方法性能实验,结果表明,57种目标化合物的方法检出限为0.03×10-6~0.39×10-6,高、中、低3组浓度水平的相对标准偏差(RSD)为0.5%~11%(n=6),空白加标回收率为80.1%~112%。方法成功应用于山东省17个采样城市环境空气样品的分析。     

Transport and distribution of artificial gamma-emitting radionuclides in the River Yenisei and its sediment

Discharges from the Krasnoyarsk Mining and Chemical Industrial Complex (KMCIC) near Krasnoyarsk resulted in radioactive contamination of sediments of the River Yenisei. Between 1999 and 2006, 16 sediment cores were collected at different positions 15-1500 km downstream from the discharge point. The concentration of artificial gamma-emitting radionuclides (¹³⁷Cs, ⁶⁰Co, ¹⁵²Eu, and ²⁴¹Am) was determined with the objective to analyze the migration processes leading to the transport of these radionuclides along the river and to their vertical distribution within the sediment. In cores taken in the vicinity of the reactors, the average activity concentration of ¹³⁷Cs, ¹⁵²Eu, and ⁶⁰Co was about 1000 Bq kg⁻¹, and the activity concentration of ²⁴¹Am was about 20 Bq kg⁻¹. Contamination levels of artificial radionuclides were decreasing with increasing distance downstream the KMCIC: The fastest decrease of average activity by a factor of 10 over a distance of 300 km was observed for ²⁴¹Am, whereas for ¹³⁷Cs this decrease occurred over a distance of 1100 km. Sequential extraction experiments revealed that in all depths and at all distances the studied radionuclides were tightly bound to the sediment.To investigate the mechanisms of transport of the ¹³⁷Cs and ⁶⁰Co contamination, mathematical models have been used to describe the contamination in the river water and within the sediments.     

臭氧氧化法处理苯酚废水的影响因素分析

将含臭氧的气体通入模拟苯酚废水,其反应过程受到很多因素的控制,比如各种反应物的投加量、投加方式、以及溶液的环境因素,如溶液pH、温度和影响反应（加速或促进）的物质存在等。文中通过实验评估各影响因素对其影响的程度,可为苯酚废水处理的实际应用提供指导和参考。     

Validation of I ecological transfer models and thyroid dose assessments using Chernobyl fallout data from the Plavsk district, Russia

Within the project “Environmental Modelling for Radiation Safety” (EMRAS) organized by the IAEA in 2003 experimental data of ¹³¹I measurements following the Chernobyl accident in the Plavsk district of Tula region, Russia were used to validate the calculations of some radioecological transfer models. Nine models participated in the inter-comparison. Levels of ¹³⁷Cs soil contamination in all the settlements and ¹³¹I/¹³⁷Cs isotopic ratios in the depositions in some locations were used as the main input information. 370 measurements of ¹³¹I content in thyroid of townspeople and villagers, and 90 measurements of ¹³¹I concentration in milk were used for validation of the model predictions.A remarkable improvement in models performance comparing with previous inter-comparison exercise was demonstrated. Predictions of the various models were within a factor of three relative to the observations, discrepancies between the estimates of average doses to thyroid produced by most participant not exceeded a factor of ten.     

Municipal solid waste management and short-term projection of the waste discard levels in Taiwan

Industrialization and urbanization result in significant changes in lifestyle. These lifestyle changes seem to lead to unsustainable consumption patterns and increase the generation of various kinds of environmental loads, especially the amount of municipal solid waste (MSW). Taiwan is a small island with scarce natural resources. The economic development in Taiwan has resulted in the generation of large amounts of MSW. As a result, the Taiwan Environmental Pollution Administration (TEPA) has produced regulations for waste minimization and has imposed several important policy measures that have successfully reduced the MSW discard rate in recent years and have established a public recycling network as a part of the MSW collection. Nowadays, the objective of the MSW policies in Taiwan is to develop a “zero-waste society.” This article aims to review the MSW management progress in Taiwan and to project future MSW discards up to 2011 based on the national plan and assumed scenarios for socioeconomic variables. According to the analysis results, a more sustainable consumption pattern can be proposed and the corresponding MSW management system can be planned so as to develop a low-waste-discard society.     

臭氧氧化法深度处理印染废水二级出水

采用臭氧氧化法深度处理印染废水二级出水,以比臭氧消耗量为基础讨论出水水质的改善情况.实验结果表明:当比臭氧消耗量为6.5 mg/mg 时,出水的吸光度在400 nm处减少90%以上,在254 nm处减少85%以上;出水的溶解性有机碳质量浓度为11.23 mg/L、COD为16.3 mg/L;臭氧分子直接氧化对降低色度和去除有机物起到一定作用,采用臭氧氧化法深度处理印染废水二级出水在技术上是可行的.     

Impact of Watershed Subdivision and Soil Data Resolution on SWAT Model Calibration and Parameter Uncertainty1

Abstract: Impact of watershed subdivision and soil data resolution on Soil Water Assessment Tool (SWAT) model calibration and parameter uncertainty is investigated by creating 24 different watershed model configurations for two study areas in northern Indiana. SWAT autocalibration tool is used to calibrate 14 parameters for simulating seven years of daily streamflow records. Calibrated parameter sets are found to be different for all 24 watershed configurations, however in terms of calibrated model output, their effect is minimal. In some cases, autocalibration is followed by manual calibration to correct for low flows, which were underestimated during autocalibration. In addition to normal validation using four years of streamflow data for each calibrated parameter set, cross‐validation (using a calibrated parameter set from one model configuration to validate observations using another configuration) is performed to investigate the effect of different model configurations on streamflow prediction. Results show that streamflow output during cross‐validation is not affected, thus highlighting the non‐unique nature of calibrated parameters in hydrologic modeling. Finally, parameter uncertainty is investigated by extracting good parameter sets during the autocalibration process. Parameter uncertainty analysis suggests that significant parameters show very narrow range of uncertainty across different watershed configurations compared with nonsignificant parameters. Results from recalibration of some configurations using only six significant parameters were comparable to that from calibration using 14 parameters, suggesting that including fewer significant parameters could reduce the uncertainty arising from model parameters, and also expedite the calibration process.     

解读摄影的本体语言

摄影本体语言是其传递视觉信息的方式,融入照相机、镜头以及成像系统最前沿的科学技术。摄影本体语言包含摄影的纪实性、瞬间性、时间与空间的拓展、镜头透视关系变化、清晰与模糊的运用等。这些视觉语言是最具摄影性质的语言,也是摄影区分其他平面艺术的要素和本质。而构图、用光、影调和色彩的表现是摄影与绘画相互交融的造型语言,是摄影视觉表达的技术与技巧。摄影本体语言和造型语言相互交融,创造影像视觉表达与表现的价值。     

Approximating SWAT Model Using Artificial Neural Network and Support Vector Machine1

Abstract: With the popularity of complex, physically based hydrologic models, the time consumed for running these models is increasing substantially. Using surrogate models to approximate the computationally intensive models is a promising method to save huge amounts of time for parameter estimation. In this study, two learning machines [Artificial Neural Network (ANN) and support vector machine (SVM)] were evaluated and compared for approximating the Soil and Water Assessment Tool (SWAT) model. These two learning machines were tested in two watersheds (Little River Experimental Watershed in Georgia and Mahatango Creek Experimental Watershed in Pennsylvania). The results show that SVM in general exhibited better generalization ability than ANN. In order to effectively and efficiently apply SVM to approximate SWAT, the effect of cross‐validation schemes, parameter dimensions, and training sample sizes on the performance of SVM was evaluated and discussed. It is suggested that 3‐fold cross‐validation is adequate for training the SVM model, and reducing the parameter dimension through determining the parameter values from field data and the sensitivity analysis is an effective means of improving the performance of SVM. As far as the training sample size, it is difficult to determine the appropriate number of samples for training SVM based on the test results obtained in this study. Simple examples were used to illustrate the potential applicability of combining the SVM model with uncertainty analysis algorithm to save efforts for parameter uncertainty of SWAT. In the future, evaluating the applicability of SVM for approximating SWAT in other watersheds and combining SVM with different parameter uncertainty analysis algorithms and evolutionary optimization algorithms deserve further research.     

AVGWLF‐Based Estimation of Nonpoint Source Nitrogen Loads Generated Within Long Island Sound Subwatersheds1

Abstract: The Generalized Watershed Loading Functions (GWLF) model and its ArcView interface (AVGWLF) were used to estimate and examine the components of the total nitrogen (TN) nonpoint source (NPS) load generated within New York and Connecticut (CT) watersheds surrounding Long Island Sound (LIS, the Sound). The majority of data used as model inputs were generally available from online sources, and the work involved an overall calibration to streamflow and TN data in accordance with generic guidelines recommended in the GWLF manual. The GWLF model performance for three calibration and two validation watersheds in CT was compared with results of a detailed model, Hydrological Simulation Program in Fortran, developed in a previous study. The results of the application illustrate the usefulness of the relatively simpler, less parameter‐intensive GWLF model in performing exploratory loading analysis in preparation for adaptive nutrient management in the LIS watersheds. The presented methodology is valuable for identification of priority watersheds for NPS pollution reduction and also for planning‐level evaluation of best management practices to achieve the desired reductions. It is estimated that ground‐water base flow may be the largest pathway for NPS TN to the Sound, contributing about 54% of the total NPS TN load, a finding with significant implications for LIS total maximum daily load reduction scenarios. In addition to ground water, septic systems are estimated to contribute about 17% of the total load, with the remaining TN load being mostly runoff from urban (17%), agricultural (5%), and low impact (e.g., forest) areas (6%).